ic: intersection cardinality

In spEDM: Spatial Empirical Dynamic Modeling

intersection cardinality

Description

intersection cardinality

Usage

## S4 method for signature 'sf'
ic(
  data,
  column,
  target,
  lib = NULL,
  pred = NULL,
  E = 2:10,
  tau = 1,
  k = E + 2,
  nb = NULL,
  threads = detectThreads(),
  parallel.level = "low",
  detrend = FALSE
)

## S4 method for signature 'SpatRaster'
ic(
  data,
  column,
  target,
  lib = NULL,
  pred = NULL,
  E = 2:10,
  tau = 1,
  k = E + 2,
  threads = detectThreads(),
  parallel.level = "low",
  detrend = FALSE
)

Arguments

data	observation data.
column	name of library variable.
target	name of target variable.
lib	(optional) libraries indices.
pred	(optional) predictions indices.
E	(optional) embedding dimensions.
tau	(optional) step of spatial lags.
k	(optional) number of nearest neighbors used.
nb	(optional) neighbours list.
threads	(optional) number of threads to use.
parallel.level	(optional) level of parallelism, low or high.
detrend	(optional) whether to remove the linear trend.

Value

A list

xmap

cross mapping performance

varname

name of target variable

method

method of cross mapping

tau

step of time lag

References

Tao, P., Wang, Q., Shi, J., Hao, X., Liu, X., Min, B., Zhang, Y., Li, C., Cui, H., Chen, L., 2023. Detecting dynamical causality by intersection cardinal concavity. Fundamental Research.

Examples

columbus = sf::read_sf(system.file("case/columbus.gpkg", package="spEDM"))

ic(columbus,"hoval","crime", k = 25)

spEDM documentation built on June 25, 2025, 9:07 a.m.